Genome-scale models in human metabologenomics
Abstract
Metabologenomics integrates metabolomics with other omics data types to comprehensively study the genetic and environmental factors that influence metabolism. These multi-omics data can be incorporated into genome-scale metabolic models (GEMs), which are highly curated knowledge bases that explicitly account for genes, transcripts, proteins and metabolites. By including all known biochemical reactions catalysed by enzymes and transporters encoded in the human genome, GEMs analyse and predict the behaviour of complex metabolic networks. Continued advancements to the scale and scope of GEMs - from cells and tissues to microbiomes and the whole body - have helped to design effective treatments and develop better diagnostic tools for metabolic diseases. Furthermore, increasing amounts of multi-omics data are incorporated into GEMs to better identify the underlying mechanisms, biomarkers and potential drug targets of metabolic diseases.
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Flux balance analysis methods have been applied to many cells, from simple bacteria to eukaryotes such as yeast and human cells, to predict fluxes through metabolic reactions.
“Flux balance analysis (FBA) methods have been applied to many cells, from simple bacteria to eukaryotes such as yeast and human cells, to predict fluxes through metabolic reactions.”
From Bringing the genetically minimal cell to life on a computer in 4D (2026) · cites this paper as [11]
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“Published online: 19 September 2024”
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Bringing the genetically minimal cell to life on a computer in 4D
Thornburg, Z. R., Maytin, A., Kwon, J., Brier, T. A., Gilbert, B. R., Fu, E., Gao, Y.-L., Quenneville, J., Wu, T., Li, H., et al. (2026) · Cell · doi:10.1016/j.cell.2026.02.009 · Cited by 44 · see citing works
- Authors
- Mardinoglu, A., & Palsson, B. Ø.
- Affiliations
- Novo Nordisk Foundation (DK)
- Corresponding author
- Palsson, Bernhard Ø.
- Venue
- Nature Reviews Genetics
- Published
- 2024-09-19
- Volume
- 26
- Issue
- 2
- Pages
- 123-140
- ISSN
- 1471-0056 (ISSN-L)
- 1471-0064
- OpenAlex
- W4402644419
- Cited by
- 54
- References
- 12
- Citations by year
- 2026: 25 · 2025: 24 · 2024: 5
- FWCI
- 2.20
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Nature Reviews Genetics (publishedVersion)
- PubMed (publishedVersion)
- Research Portal (King's College London) (submittedVersion)
- Technical University of Denmark, DTU Orbit (Technical University of Denmark, DTU) (submittedVersion)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Microbial Metabolic Engineering and Bioproduction
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Keywords
- genome-scale metabolic models, multi-omics integration, metabolic disorders, metabolic networks, human microbiome, biomarkers, therapeutic target, metabolic disease diagnosis
- MeSH terms
- Humans, Metabolic Diseases, Genome, Human, Genomics, Metabolic Networks and Pathways, Metabolomics, Metabolome
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